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Record W2910229208 · doi:10.2217/nmt-2018-0031

Person-Centered Risk Assessment Framework: Assessing and Managing Risk in Older Adults Living With Dementia

2019· article· en· W2910229208 on OpenAlexaff
Linda Lee, Loretta M. Hillier, Stephanie K. Lu, Sharon D Martin, Sarah Pritchard, Jennifer Amy Janzen, Karen Slonim

Bibliographic record

VenueNeurodegenerative Disease Management · 2019
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsSt. Peter's HospitalMcMaster UniversityCentre for Family Medicine
Fundersnot available
KeywordsDementiaRisk assessmentHealth careNursingMedicinePsychologyDisease

Abstract

fetched live from OpenAlex

AIM: This study pilot-tested the person-centered risk assessment framework (PCRAF), a framework for managing risk among persons living with dementia (PLWD) in primary care. METHODS: Healthcare providers (N = 7) piloting the PCRAF completed a survey, rating their satisfaction with the tool, and an interview to gather their perceptions of the PCRAF. PLWD and care partners (N = 12) completed a survey, rating their satisfaction with safety planning. RESULTS: Care providers were very satisfied with the tool; however, patient or care partner inability to perceive or understand safety risks was a challenge. Use of the PCRAF was perceived as an opportunity to empower self-management, gather PLWD and care partner perspectives, reduce burden for care partners and increase understanding of potential risks. Patients and care partners were very satisfied with the way in which they were included in the risk discussion. CONCLUSION: The PCRAF is a promising new tool to reduce risks associated with dementia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.289
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations29
Published2019
Admission routes1
Has abstractyes

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